Object-level Perception Sharing Among Connected Vehicles

Advances in vehicular communication technologies have made Connected Vehicles (CVs) a near-term reality. Compared to models where vehicles rely solely on their own perception to sense and make decision on the environment, CVs have the potential to allow information sharing among vehicles to improve sensing and decision making collectively. A first concrete step towards this goal is enabling vehicles to share perception-related information, to overcome limitations of their respective sensors (e.g., partial awareness due to occlusions). Sharing processed information vs raw sensor data has the advantage of reducing the amount of data to be transmitted, and the required computation burden at the receiver side.This paper proposes an approach to enable object-level sharing among vehicles. Following state-of-the-art object-level management techniques, we developed a two-layer architecture that handles object tracking and fusion from dynamic remote sources of information. We implemented our approach and showed that it can achieve realistic performance, and robustness both in terms of quality of information and computation.